Abstract
A hierarchical neurocontroller architecture consisting of two artificial neural network systems for the manipulation of a robotic arm is presented. The higher-level neural system participates in the delineation of the robot arm workspace and coordinates transformation and the motion decision-making process. The lower one provides the correct sequence of control actions. The capabilities, including speed, adaptability, and computational efficiency, of the developed architecture are illustrated by an example.
Recommended Citation
X. J. Avula and L. C. Rabelo, "Hierarchical Neurocontroller Architecture for Intelligent Robotic Manipulation," Proceedings of the 1991 IEEE International Conference on Robotics and Automation, 1991, Institute of Electrical and Electronics Engineers (IEEE), Jan 1991.
The definitive version is available at https://doi.org/10.1109/ROBOT.1991.132030
Meeting Name
1991 IEEE International Conference on Robotics and Automation, 1991
Department(s)
Mechanical and Aerospace Engineering
Keywords and Phrases
Adaptability; Artificial Neural Network Systems; Computational Efficiency; Control Actions Sequence; Delineation; Hierarchical Neurocontroller Architecture; Hierarchical Systems; Higher-Level Neural System; Intelligent Robotic Manipulation; Motion Decision-Making Process; Neural Nets; Position Control; Robots; Speed; Transformation; Workspace
Document Type
Article - Conference proceedings
Document Version
Final Version
File Type
text
Language(s)
English
Rights
© 1991 Institute of Electrical and Electronics Engineers (IEEE), All rights reserved.
Publication Date
01 Jan 1991
